Research on the milling tool monitoring system based on wavelet neural network
among the milling process, the signal representation tools sharply wearing in primary stage, is weaker. While the work piece accuracy have already at this time obvious change. Wavelet neural network can effectively handle various signals with different frequency, but it is possible that it can not detect the faint signal. Based on monitoring accuracy change of the workpiece, do modify the parameter of wavelet transform in time, and it can enhance the ability of monitoring faint signal, decrease missing rate and false alarm rate.
The milling Cutter Monitoring Wavelet neural network
Guizhong Guo Xinhua Mao
Xinxiang University Xinxiang, Henan Province of China Henan Institute ofScience and Technology Xinxiang, Henan Province of China
国际会议
哈尔滨
英文
1421-1423
2011-08-12（万方平台首次上网日期，不代表论文的发表时间）